1. Field of the Invention
The present invention relates to image compression using lossy compression, and more particularly, to the formation of a composite image from images selected such that the compression of the selected images as part of the composite image results in an improvement in quality for at least one of the selected images.
2. Description of the Related Art
Image data may be represented digitally for storage and manipulation using a computer system. In addition, digital image data may be transferred between computer systems via a network. In order to reduce the amount of computing resources needed (e.g., for storage and transmission), various compression schemes have been used to reduce the size of an image file.
In general, a compression scheme encodes the data with the desired result being a reduction in the size of the data. A complimentary decompression scheme is then used to decompress the compressed data. There are two general types of compression: lossy and lossless. Using lossless compression, data can be compressed and then decompressed without any loss in data. However, with lossy compression, some data may be lost as a result of compressing and decompressing the data.
It is a requirement with certain data, such as financial data, that there be unity between the original and decompressed versions. However, where some degree of data loss is acceptable with image data, lossy compression can be used to compress digital image data.
In lossy compression, there is a tradeoff between retention of image quality (after image decompression) and compressed file size. That is, as the rate of compression increases, the likelihood of data loss increases thereby reducing the quality of the resulting image upon decompression. For example, the likelihood for data loss tends to be greater when an image is compressed to a tenth of its original size than when it is reduced to a fifth of its size.
The content and characteristics of the image can affect the compressibility of the image. For example, an image's compressibility can depend on the number of transitions within the image (i.e., the busyness of the image). That is, the fewer the number of transitions, the better the compressibility.
When compressing an image, it would therefore be beneficial to be able to “take advantage of” a compressibility of one image to improve on the compressibility of another image.